Augmented reality navigation for liver surgery: an enhanced coherent point drift algorithm based hybrid optimization scheme

Augmented reality (AR) based bowel or liver surgery still has not been implemented successfully due to limitations of accurate and proper image registration of uterus and gallbladder during surgery. This research aims to improve target registration error, which helps to navigate through hidden uterus and gallbladder during surgery. Therefore, it will reduce risk of cutting uterus or common bile duct during surgery, which can be fatal and cause devastating effects on the patient. The proposed system integrates the enhanced Coherent Point Drift (CPD) Algorithm with hybrid optimization scheme that incorporates Nelder-Mead simplex and genetic algorithm, to optimize the obtained weight parameter, which in turns improves the target image registration error and processing time of image registration. The system has minimized the target registration error by 0.31 mm in average. It provides a substantial accuracy in terms of target registration error, where the root mean square error is enhanced from 1.28 +/- 0.68 mm to 0.97 +/- 0.41 mm and improves processing time from 16 similar to 18 ms/frame to 11 similar to 12 ms/frame. The proposed system is focused on improving the accuracy of deformable image registration accuracy of soft tissues and hidden organs, which then helps in proper navigation and localization of the uterus hidden behind bowel and gallbladder hidden behind liver.